package ostat

import (
	"errors"
	"math"
)

// from http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Online_algorithm

type OnlineStat struct {
	n    int64
	mean float64
	m2   float64
	Max  float64
	Min  float64
}

func NewOnlineStat() *OnlineStat {
	return &OnlineStat{
		Min: math.Inf(1),
		Max: math.Inf(-1),
	}
}

func (os *OnlineStat) Push(v float64) {
	os.n += 1
	if v < os.Min {
		os.Min = v
	}
	if v > os.Max {
		os.Max = v
	}

	delta := v - os.mean
	os.mean = os.mean + delta/float64(os.n)
	os.m2 = os.m2 + delta*(v-os.mean)
}

func (os *OnlineStat) Mean() (float64, error) {
	if os.n == 0 {
		return 0.0, errors.New("no data")
	}
	return os.mean, nil
}

func (os *OnlineStat) Variance() (float64, error) {
	if os.n == 0 {
		return 0.0, errors.New("no data")
	}
	return os.m2 / float64(os.n-1), nil
}

func (os *OnlineStat) StdDev() (float64, error) {
	variance, err := os.Variance()
	return math.Sqrt(variance), err
}